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研究生:郭俊傑
研究生(外文):Chon-Kit Kuok
論文名稱:多感測模態機器人之人物辨識及跟隨
論文名稱(外文):Human Recognition and Following of a Robot with Multi-Sensing Models
指導教授:黃漢邦黃漢邦引用關係
口試委員:趙儀珊林顯達林沛群黃心健
口試日期:2016-07-15
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:機械工程學研究所
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:2016
畢業學年度:104
語文別:英文
論文頁數:71
中文關鍵詞:使用者辨識人機互動跟隨行動式機器人多模態融合
外文關鍵詞:User RecognitionHuman-Robot InteractionFollowingMobile RobotMultimodal Fusion
相關次數:
  • 被引用被引用:1
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  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:1
近年來,機器人已經融入人類生活中,而服務型機器人的發展是為了讓人類的生活更舒適便利。與此同時,機器人也不只是單純的機器,機器人應該具備與人互動以及在環境順暢移動的能力。本篇論文旨在發展一個跟隨機器人,此機器人能夠跟隨特定使用者,並能自動搜尋此使用者。我們使用SLAMMOT使機器人能了解自身週遭環境位置,以及使用者的位置。當機器人丟失跟隨目標時,機器人能尋找使用者,令使用者能重新進入機器人的視線後重新跟隨。
本篇論文也提出使用者的辨認方法,讓機器人能夠辨識特定使用者,使機器人不會認錯要跟踪的使用者。所建構的跟隨機器人系統,經實驗驗證具有不錯的效果。


In recent years, robots are assimilated into humans’ life. Service robots are built for making people more convenient and more comfortable. A robot is not just a machine. It should be capable of interacting with people appropriately and moving in the surroundings smoothly. This thesis attempts to develop a shopping assistant robot system. It can recognize a specific user, automatically follow him and search for him. SLAMMOT is used in the robot for understanding environments, localizing itself and locating the user. If the robot loses the tracking user, it searches for the user and causes the user can be found in the view of the robot. In addition, the human recognition system is constructed to recognize the specific user. The proposed system has been justified in experiments. The results are promising.

誌謝 ii
摘要 iv
Abstract vi
List of Tables xii
List of Figures xiv
Chapter 1 Introduction 1
1.1 Motivation 1
1.2 Related Works 2
1.3 Objectives and Contributions 3
1.4 Thesis Organization 4
Chapter 2 Recognition and Tracking a Specific Target 7
2.1 Human Following Algorithm 8
2.2 Multimodal User Recognition 12
2.2.1 Face Modality 13
2.2.2 Body Size Modality 20
2.2.3 Dress Color Modality 25
2.2.4 User Identification System and Multimodal fusion 29
2.3 Summary 36
Chapter 3 Following, Guiding and User Re-Tracking 39
3.1 Human Following System 39
3.2 User Re-Tracking 40
3.2.1 User Re-tracking mechanism 40
3.2.2 User Re-tracking Searching Scenario 42
3.4 Summary 44
Chapter 4 Simulations and Experiments 47
4.1 Software Platform 47
4.2 Hardware Platform 47
4.3 Experimental Results 49
4.3.1 Case Study 1: Multimodal user recognition 50
4.3.2 Case Study 2: Following a Specific User 54
4.3.3 Case Study 3: User Re-Tracking 59
4.4 Summary 62
Chapter 5 Conclusions and Future Works 65
5.1 Conclusions 65
5.2 Future Works 66
References 67


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